Selective streaming of video segments based on buffer data and download rate range

ABSTRACT

Technologies for selectively streaming video based on mapping buffer data to download rates. The technologies can include sampling download rates of a video player prior to or during downloading of a first video segment to the video player. The technologies can include determining a range of download rates of the video player based at least on the sampled download rates. The technologies can include determining an amount of accumulated video data in a buffer of the video player immediately prior to or during the downloading of the first video segment. Also, the technologies can include mapping the determined amount of accumulated video data to a download rate within the determined range of download rates using a mapping function, and determining a second video segment quality for a second video segment based at least on the mapped download rate.

CROSS REFERENCE TO RELATED APPLICATIONS

This application is a continuation of, and claims priority from,co-pending U.S. patent application Ser. No. 16/225,194, filed Dec. 19,2018, entitled SELECTIVE STREAMING OF VIDEO SEGMENTS BASED ON BUFFERDATA AND DOWNLOAD RATE RANGE, the contents of which are herebyincorporated by reference.

COPYRIGHT PROTECTION

This application includes material that is subject to copyrightprotection. The copyright owner has no objection to the facsimilereproduction by anyone of the patent disclosure, as it appears in thePatent and Trademark Office files or records, but otherwise reserves allcopyright rights whatsoever.

FIELD

The present disclosure relates to selectively streaming video based onbuffer data and download rates. Also, the present disclosure relates torange based adaptive bitrate processes for selective streaming ofdigital video segments.

BACKGROUND

Adaptive bitrate and bandwidth estimator processes can be advantageouslyused with digital video players that stream video segments. Suchprocesses can be used for choosing future video segment qualities in avideo stream. Adaptive bitrate processes typically make decisions basedon an amount of accumulated video data in an internal buffer of a videoplayer and a bandwidth estimation supplied by a bandwidth estimatorprocess. Typically, bandwidth estimator processes return an estimationof bandwidth as a single number that is determined using some functionapplied on bandwidth samples usually collected over a few minutes beforeselection of a next video segment quality. This can be useful to theplaying of streaming video since an output of such a function can beused as input for the video player to adapt to changes in networkbandwidth. And, the adaptations can improve the experience of viewingstreaming video by reducing rebuffering delays and unnecessary drops invideo segment quality or pixel resolution.

However, the bandwidth of a network can vary significantly over time;hence, the single number approach, used by conventional adaptive bitrateand bandwidth estimator processes, may not give an adequateidentification of past and current network behavior. Therefore, digitalvideo players relying on such conventional adaptive bitrate andbandwidth estimator processes may have more rebuffering delays andunnecessary drops in video segment quality or pixel resolution thandesired. With the bandwidth estimation processes and heuristictechniques currently used, there is no good way to distinguish betweenstable and unstable networks that have about the same average bandwidth.However, while for the stable networks the average bandwidth is a goodestimation for the immediate future behavior, for an unstable networkthe actual bandwidth can be significantly higher or significantly lowerthan the estimation of bandwidth from conventional adaptive bitrate andbandwidth estimator processes. Thus, leading the adaptive bitrate andbandwidth estimator processes to bad decisions in selecting next or,more generally speaking, future video segment quality.

One known improved solution is disclosed in U.S. Pat. No. 10,116,715,issued on Oct. 30, 2018 and titled “Adapting Encoded Bandwidth”, whichdiscloses percentiles of bandwidth history and using the percentiles todefine a range of bandwidth to operate in. The aforesaid techniquesdescribed in U.S. Pat. No. 10,116,715 consider bandwidth minimum floorand maximum cap as well as recency to estimate bandwidth. This mayimprove the aforementioned conventional techniques, but there stillremain technical problems associated with adaptive bitrate and bandwidthestimator processes.

SUMMARY

Factoring in video player buffer use information and accumulated data inthe buffer can improve adaptive bitrate and bandwidth estimatorprocesses. Such additional factors are not considered by U.S. Pat. No.10,116,715 and present a technical deficiency in the art. Describedherein are improved systems and methods for selectively streaming videothat can overcome at least the technical problems mentioned in thebackground section above. The systems and methods for selectivelystreaming video are based on buffer data and download rates as well asimproved range based adaptive bitrate processes for selectivelystreaming digital video. The improved range based adaptive bitrateprocesses leverage mapping buffer data with ranges of download rates tochoose future video segment quality (such as to choose next videosegment quality). In summary, examples of the systems and methodsdisclosed herein for selectively streaming video provide specifictechnical solutions to at least the technical problems mentioned in thebackground section and other parts of the application as well as othertechnical problems not described herein but recognized by those of skillin the art.

In general, embodiments disclosed herein can overcome such technicalproblems using at least a combined technical solution of: (1) usingrange based adaptive bitrate processes to determine a bandwidth range,and (2) mapping buffer data to a download rate within the determinedbandwidth range using a mapping function. With the technical solutionherein, choosing future video segment quality, such as next videosegment quality, becomes more reliable in that, for example, theselection of the video segment quality is based on the mapped downloadrate and therefore based on a range of download rates instead of asingle averaged value—which is the case for conventional techniques.

The new and improved solution considers the aberrations of networkbandwidth. In some embodiments, instead of using known types ofbandwidth estimation or averaging, the new and useful technologies useaccumulated statistical data on network bandwidth. This includesconsidering the aberrations in the bandwidth. The techniques can alsoinclude calculating percentiles over download rate samples. Thecalculated percentiles can then be used instead of a single estimated oraveraged download rate to select a future video segment quality. Inaddition, the technologies can choose bitrate by mapping the bufferstate to the range instead of mapping to a discrete bitrate. And, fromthe range, a corresponding bitrate can be selected for mapping to avideo segment quality.

In short, the methods and systems described herein use a range ofnumbers rather than a single number because it has been found that arange of values can give a better classification of a network'sbandwidth (with its aberrations) than a single number. Indeed, for twonetworks with the same average bandwidth, the more fluctuating andunstable network produces wider range of bandwidth. Fortunately, thetechnical solutions described herein can make more intelligentadaptations for the less stable network.

Additionally, history of samples of download rates for a video player orrelated device can be stored and used to make the determinations ofdownload rate range. Also, the stored download rate samples can be usedto calculate percentiles for those samples. And, then the percentilescan be used as input to define a range of download rates for the mappingfunctionality. To put it another way, the percentiles can be used as abasis for the defined range that can serve as an input for an adaptivebitrate process, which, in turn, choses a download rate value within therange based on internal buffer occupancy of the video player mapped tothe range. The download rate chosen from the range can then be mapped toa video segment quality. Also, additional parameters can be used tofurther refine the selection of the future video segment quality. Thus,the systems and methods provide a novel and technical way of usingdownload rate statistical data, which can include bandwidth aberrations,to establish the range of possible bandwidth values and to map theplayer buffer occupancy to a value in the range; and, in turn, choosethe video segment quality according to the value in the range.

In accordance with one or more embodiments, this disclosure providescomputerized methods for selectively streaming digital video, as well asa non-transitory computer-readable storage medium for carrying outtechnical steps of the computerized methods. The non-transitorycomputer-readable storage medium has tangibly stored thereon, ortangibly encoded thereon, computer readable instructions that whenexecuted by one or more devices (e.g., application server, transactionsserver, client device, and the like) cause at least one processor toperform a method for a novel and improved selective streaming of digitalvideo.

In accordance with one or more embodiments, a system is provided thatincludes one or more computing devices configured to providefunctionality in accordance with one or more embodiments of a novel andimproved way of selectively streaming digital video.

In accordance with one or more embodiments, functionality is embodied insteps of a method performed by at least one computing device. Inaccordance with one or more embodiments, program code (or program logic)executed by processor(s) of a computing device to implementfunctionality in accordance with one or more embodiments describedherein is embodied in, by and/or on a non-transitory computer-readablemedium.

BRIEF DESCRIPTION OF THE DRAWINGS

The foregoing and other objects, features, and advantages of thedisclosure will be apparent from the following description ofembodiments as illustrated in the accompanying drawings, in whichreference characters refer to the same parts throughout the variousviews. The drawings are not necessarily to scale, emphasis instead beingplaced upon illustrating principles of the disclosure:

FIG. 1 is a schematic diagram illustrating an example of a network(which includes elements that can implement selectively streaming videobased on buffer data and download rates) within which systems andmethods disclosed herein can be implemented according to someembodiments of the present disclosure;

FIG. 2 is a schematic diagram illustrating an example of a computingdevice, in accordance with some embodiments of the present disclosure;

FIGS. 3-5 are flowcharts illustrating example methods, in accordancewith some embodiments of the present disclosure; and

FIGS. 6-9 are schematic diagrams illustrating example operations inaccordance with some specific implementations of some embodiments of thepresent disclosure.

DESCRIPTION OF EMBODIMENTS

The present disclosure will now be described more fully hereinafter withreference to the accompanying drawings, which form a part hereof, andwhich show, by way of illustration, certain example embodiments. Subjectmatter may, however, be embodied in a variety of different forms and,therefore, covered or claimed subject matter is intended to be construedas not being limited to any example embodiments set forth herein;example embodiments are provided merely to be illustrative. Likewise, areasonably broad scope for claimed or covered subject matter isintended. Among other things, for example, subject matter may beembodied as methods, devices, components, or systems. Accordingly,embodiments may, for example, take the form of hardware, software,firmware or any combination thereof (other than software per se). Thefollowing detailed description is, therefore, not intended to be takenin a limiting sense.

Throughout the specification and claims, terms may have nuanced meaningssuggested or implied in context beyond an explicitly stated meaning.Likewise, the phrase “in one embodiment” as used herein does notnecessarily refer to the same embodiment and the phrase “in anotherembodiment” as used herein does not necessarily refer to a differentembodiment. It is intended, for example, that claimed subject matterinclude combinations of example embodiments in whole or in part.

In general, terminology may be understood at least in part from usage incontext. For example, terms, such as “and”, “or”, or “and/or,” as usedherein may include a variety of meanings that may depend at least inpart upon the context in which such terms are used. Typically, “or” ifused to associate a list, such as A, B or C, is intended to mean A, B,and C, here used in the inclusive sense, as well as A, B or C, here usedin the exclusive sense. In addition, the term “one or more” as usedherein, depending at least in part upon context, may be used to describeany feature, structure, or characteristic in a singular sense or may beused to describe combinations of features, structures or characteristicsin a plural sense. Similarly, terms, such as “a,” “an,” or “the,” again,may be understood to convey a singular usage or to convey a pluralusage, depending at least in part upon context. In addition, the term“based on” may be understood as not necessarily intended to convey anexclusive set of factors and may, instead, allow for existence ofadditional factors not necessarily expressly described, again, dependingat least in part on context.

The present disclosure is described below with reference to blockdiagrams and operational illustrations of methods and devices. It isunderstood that each block of the block diagrams or operationalillustrations, and combinations of blocks in the block diagrams oroperational illustrations, can be implemented by means of analog ordigital hardware and computer program instructions. These computerprogram instructions can be provided to a processor of a general-purposecomputer to alter its function as detailed herein, a special purposecomputer, ASIC, or other programmable data processing apparatus, suchthat the instructions, which execute via the processor of the computeror other programmable data processing apparatus, implement thefunctions/acts specified in the block diagrams or operational block orblocks. In some alternate implementations, the functions/acts noted inthe blocks can occur out of the order noted in the operationalillustrations. For example, two blocks shown in succession can in factbe executed substantially concurrently or the blocks can sometimes beexecuted in the reverse order, depending upon the functionality/actsinvolved.

These computer program instructions can be provided to a processor of: ageneral purpose computer to alter its function to a special purpose; aspecial purpose computer; ASIC; or other programmable digital dataprocessing apparatus, such that the instructions, which execute via theprocessor of the computer or other programmable data processingapparatus, implement the functions/acts specified in the block diagramsor operational block or blocks, thereby transforming their functionalityin accordance with embodiments herein.

For the purposes of this disclosure a computer readable medium (orcomputer-readable storage medium/media) stores computer data, which datacan include computer program code (or computer-executable instructions)that is executable by a computer, in machine readable form. By way ofexample, and not limitation, a computer readable medium can includecomputer readable storage media, for tangible or fixed storage of data,or communication media for transient interpretation of code-containingsignals. Computer readable storage media, as used herein, refers tophysical or tangible storage (as opposed to signals) and includeswithout limitation volatile and non-volatile, removable andnon-removable media implemented in any method or technology for thetangible storage of information such as computer-readable instructions,data structures, program modules or other data. Computer readablestorage media includes, but is not limited to, RAM, ROM, EPROM, EEPROM,flash memory or other solid-state memory technology, CD-ROM, DVD, orother optical storage, magnetic cassettes, magnetic tape, magnetic diskstorage or other magnetic storage devices, or any other physical ormaterial medium which can be used to tangibly store the desiredinformation or data or instructions and which can be accessed by acomputer or processor.

For the purposes of this disclosure the term “server” should beunderstood to refer to a service point which provides processing,database, and communication facilities. By way of example, and notlimitation, the term “server” can refer to a single, physical processorwith associated communications and data storage and database facilities,or it can refer to a networked or clustered complex of processors andassociated network and storage devices, as well as operating softwareand one or more database systems and application software that supportthe services provided by the server. Servers can vary widely inconfiguration or capabilities, but generally a server can include one ormore central processing units and memory. A server can also include oneor more mass storage devices, one or more power supplies, one or morewired or wireless network interfaces, one or more input/outputinterfaces, or one or more operating systems, such as Windows Server,Mac OS X, Unix, Linux, FreeBSD, or the like.

For the purposes of this disclosure a “network” should be understood torefer to a network that can couple devices so that communications can beexchanged, such as between a server and a client device or other typesof devices, including between wireless devices coupled via a wirelessnetwork, for example. A network can also include mass storage, such asnetwork attached storage (NAS), a storage area network (SAN), or otherforms of computer or machine-readable media, for example. A network caninclude the Internet, one or more local area networks (LANs), one ormore wide area networks (WANs), wire-line type connections, wirelesstype connections, cellular or any combination thereof. Likewise,sub-networks, which can employ differing architectures or can becompliant or compatible with differing protocols, can interoperatewithin a larger network. Various types of devices can, for example, bemade available to provide an interoperable capability for differingarchitectures or protocols. As one illustrative example, a router canprovide a link between otherwise separate and independent LANs.

A communication link or channel can include, for example, analogtelephone lines, such as a twisted wire pair, a coaxial cable, full orfractional digital lines including T1, T2, T3, or T4 type lines,Integrated Services Digital Networks (ISDNs), Digital Subscriber Lines(DSLs), wireless links including satellite links, or other communicationlinks or channels, such as can be known to those skilled in the art.Furthermore, a computing device or other related electronic devices canbe remotely coupled to a network, such as via a wired or wireless lineor link, for example.

A computing device can be capable of sending or receiving signals, suchas via a wired or wireless network, or can be capable of processing orstoring signals, such as in memory as physical memory states, and can,therefore, operate as a server. Thus, devices capable of operating as aserver can include, as examples, dedicated rack mounted servers, desktopcomputers, laptop computers, set top boxes, integrated devices combiningvarious features, such as two or more features of the foregoing devices,or the like. Servers can vary widely in configuration or capabilities,but generally a server can include one or more central processing unitsand memory. A server can also include one or more mass storage devices,one or more power supplies, one or more wired or wireless networkinterfaces, one or more input/output interfaces, or one or moreoperating systems, such as Windows Server, Mac OS X, Unix, Linux,FreeBSD, or the like.

For purposes of this disclosure, a client (or consumer or user) devicecan include a computing device capable of sending or receiving signals,such as via a wired or a wireless network. A client device can, forexample, include a desktop computer or a portable device, such as acellular telephone, a smart phone, a display pager, a radio frequency(RF) device, an infrared (IR) device, an NFC device, a Personal DigitalAssistant (PDA), a handheld computer, a tablet computer, a phablet, alaptop computer, a set top box, a wearable computer, smart watch, anintegrated or distributed device combining various features, such asfeatures of the forgoing devices, or the like.

A client device can vary in terms of capabilities or features. Claimedsubject matter is intended to cover a wide range of potentialvariations. For example, a simple smart phone, phablet or tablet caninclude a numeric keypad or a display of limited functionality, such asa monochrome liquid crystal display (LCD) for displaying text. Incontrast, however, as another example, a web-enabled client device caninclude a high-resolution screen, one or more physical or virtualkeyboards, mass storage, one or more accelerometers, one or moregyroscopes, global positioning system (GPS) or otherlocation-identifying type capability, or a display with a high degree offunctionality, such as a touch-sensitive color 2D or 3D display, forexample.

A client device can include or can execute a variety of operatingsystems, including a personal computer operating system, such as aWindows, iOS or Linux, or a mobile operating system, such as iOS,Android, or Windows Mobile, or the like.

A client device can include or can execute a variety of possibleapplications, such as a client software application enablingcommunication with other devices, such as communicating one or moremessages, such as via email, for example Yahoo!® Mail, short messageservice (SMS), or multimedia message service (MMS), for example Yahoo!Messenger®, including via a network, such as a social network,including, for example, Tumblr®, Facebook®, LinkedIn®, Twitter®,Flickr®, or Google+®, Instagram™, to provide only a few possibleexamples. A client device can also include or execute an application tocommunicate content, such as, for example, textual content, multimediacontent, or the like. A client device can also include or execute anapplication to perform a variety of possible tasks, such as browsing,searching, playing, streaming or displaying various forms of content,including locally stored or uploaded images and/or video, or games (suchas fantasy sports leagues). The foregoing is provided to illustrate thatclaimed subject matter is intended to include a wide range of possiblefeatures or capabilities.

In general, embodiments disclosed herein can overcome technical problemsassociated with streaming video segments using a combined technicalsolution of: (1) using range based adaptive bitrate processes, and (2)mapping buffer data to a download rate within a determined range ofdownload rates using a mapping function. With the technical solution,choosing next or future video segment quality for a next or future videosegment to be downloaded becomes more reliable in that for example theselection of the video segment quality is based on the mapped downloadrate and therefore based on a range of download rates instead of asingle estimated or average rate. The technical solution considers theaberrations of network bandwidth.

The systems and methods disclosed herein can rely on a ranged basedadaptive bitrate process and/or a range based bandwidth estimatorprocess, rather than calculating a single number as a bandwidthestimation. Assuming that future network behavior does not differ muchfrom the immediate past, the range describes the network conditions muchbetter than the single estimated number which is the output ofconventional adaptive bitrate and bandwidth estimator processes. Inaddition to the range based techniques, the systems and method can mapthe player buffer state to the range and choose the bitrate according tothe results of the mapping. The decisions of an adaptive bitrate processthat uses a range of values and the aforesaid mapping can achieve muchmore effective selective streaming of digital video. Also, suchtechniques can choose to stay on the safe side, going to the lower endof the range if the video buffer is empty, or to the higher end, if thebuffer is full and the adaptive bitrate is set for higher risk, butstill staying in the range of the usual network performance. Withoutusing a range as input for the mapping, the adaptive bitrate can fallinto unnecessary extremities, falling to a lowest bitrate available whenthe buffer is empty or jumping to a too high bitrate when the buffer isalmost full.

The systems and methods can include sampling download rates of a videoplayer prior to or during downloading of a first video segment (e.g., acurrent video segment) to the video player. The systems and methods canalso include determining a range of download rates of the video playerbased at least on the sampled download rates. The technologies caninclude determining an amount of accumulated video data in a buffer ofthe video player immediately prior to or during the downloading of thefirst video segment. Also, the technologies can include mapping theamount of accumulated video data to a download rate within thedetermined range of download rates using a mapping function. And, themethods and systems can finally include determining a second videosegment quality (e.g., a next video segment quality or another futurevideo segment quality) for a second video segment (e.g., a next videosegment or another future video segment) to be downloaded after thedownloading of the first video segment based at least on the mappeddownload rate.

Certain embodiments will now be described in greater detail withreference to the figures. In general, with reference to FIG. 1 , asystem 100 in accordance with an embodiment of the present disclosure isshown. FIG. 1 shows components of a general environment in which thesystems and methods discussed herein can be practiced. Not all thecomponents can be required to practice the disclosure, and variations inthe arrangement and type of the components can be made without departingfrom the spirit or scope of the disclosure. As shown, system 100 of FIG.1 includes local area networks (“LANs”)/wide area networks(“WANs”)—network 105 and client devices 102-104 (e.g., such as handheldor mobile devices, Internet of Things devices, etc.). Streaming videosegments can be downloaded over network 105 by client devices (such asclient devices 102-104) for digital video players stored and executed onthe devices (such as the enhanced digital video player describedherein).

As shown, system 100 of FIG. 1 also includes video content server 106communicatively coupled to database 108 used by the content server, andvideo service server 110 that can persistently store the enhanced videoplayer described herein and can provide the enhanced video player toother computing devices for being stored in memory of those devices orpersistently stored in those devices. Also, as shown, system 100 of FIG.1 includes database 112 communicatively coupled to video service server110 and used by the video service server, and a third server 114communicatively coupled to database 116 use by the third server. Thedatabases described herein can be used by the servers to select, storeand organize data used as input for the processes described herein. Theclient devices described herein can also select and use the data storedand organized in the databases as input for the processes describedherein.

It is to be understood that the processes described herein can beexecuted by one or more of the client devices and servers disclosedherein. Specifically, for example, each of the servers 106, 110, and 114can include a device that includes a configuration to perform at leastsome of the operations of process 300 depicted in FIG. 3 and alternativesub-processes of process 300 illustrated in FIGS. 4 and 5 . Also, forexample, each of the client devices 102-104 can include a device thatincludes a configuration to perform at least some of the operations ofprocess 300 depicted in FIG. 3 and alternative sub-processes of process300 illustrated in FIGS. 4 and 5 . Example embodiments of client devices102-104 and servers 106, 110, and 114 are described in more detailbelow.

Generally, client devices 102-104 can include virtually any computingdevice capable of receiving and sending a message over a network, suchas network 105—which could include a wireless network—, or the like.Client devices 102-104 can also be mobile devices that are configured tobe portable and held in a hand or two hands. Such devices includemulti-touch and portable devices such as, cellular telephones, smartphones, display pagers, radio frequency (RF) devices, infrared (IR)devices, Personal Digital Assistants (PDAs), handheld computers, laptopcomputers, wearable computers, smart watch, tablet computers, phablets,integrated devices combining one or more of the preceding devices, andthe like. As such, mobile devices typically range widely in terms ofcapabilities and features. For example, a cell phone can have a numerickeypad and a few lines of monochrome LCD display on which only text canbe displayed. In another example, a web-enabled mobile device can have atouch sensitive screen, a stylus, and an HD display in which both textand graphics can be displayed.

A web-enabled client device can include a browser application that isconfigured to receive and to send web pages, web-based messages, and thelike. The browser application can be configured to receive and displaygraphics, text, multimedia, and the like, employing virtually any webbased language, including a wireless application protocol messages(WAP), and the like. In one embodiment, the browser application isenabled to employ Handheld Device Markup Language (HDML), WirelessMarkup Language (WML), WMLScript, JavaScript, Standard GeneralizedMarkup Language (SMGL), HyperText Markup Language (HTML), eXtensibleMarkup Language (XML), and the like, to display and send a message.

Client devices 102-104 and the servers 106, 110, and 114 can eachinclude at least one client application that is configured to receivecontent or data from another computing device. The client applicationcan include a capability to provide and receive textual content,graphical content, audio content, authentication and keying information,and the like. The client application can further provide informationthat identifies itself, including a type, capability, name, and thelike. In one embodiment, client devices 102-104 and the servers 106,110, and 114 can each uniquely identify themselves through any of avariety of mechanisms. Client devices can be identifiable via a phonenumber, Mobile Identification Number (MIN), an electronic serial number(ESN), or another type of device identifier. Servers can be identifiablevia an electronic serial number (ESN) or another type of deviceidentifier.

In general, client devices 102-104 and servers 106, 110, and 114 can becapable of sending or receiving signals, such as via a wired or wirelessnetwork, or can be capable of processing or storing signals, such as inmemory as physical memory states.

Network 105 is configured to couple devices 102-104 and servers 106,110, and 114, or the like, with other computing devices. Network 105 isenabled to employ any form of computer readable media for communicatinginformation from one electronic device to another. Also, network 105 caninclude the Internet in addition to local area networks (LANs), widearea networks (WANs), direct connections, such as through a universalserial bus (USB) port, other forms of computer-readable media, or anycombination thereof. On an interconnected set of LANs, including thosebased on differing architectures and protocols, a router acts as a linkbetween LANs, enabling messages to be sent from one to another, and/orother computing devices.

Within the communications networks utilized or understood to beapplicable to the present disclosure, such networks will employ variousprotocols that are used for communication over the network. Signalpackets communicated via a network, such as a network of participatingdigital communication networks, can be compatible with or compliant withone or more protocols. Signaling formats or protocols employed caninclude, for example, TCP/IP, UDP, QUIC (Quick UDP Internet Connection),DECnet, NetBEUI, IPX, APPLETALK™, or the like. Versions of the InternetProtocol (IP) can include IPv4 or IPv6. The Internet refers to adecentralized global network of networks. The Internet includes localarea networks (LANs), wide area networks (WANs), wireless networks, orlong haul public networks that, for example, allow signal packets to becommunicated between LANs. Signal packets can be communicated betweennodes of a network, such as, for example, to one or more sites employinga local network address. A signal packet can, for example, becommunicated over the Internet from a user site via an access nodecoupled to the Internet. Likewise, a signal packet can be forwarded vianetwork nodes to a target site coupled to the network via a networkaccess node, for example. A signal packet communicated via the Internetcan, for example, be routed via a path of gateways, servers, etc. thatcan route the signal packet in accordance with a target address andavailability of a network path to the target address.

In some embodiments, the network 105 can include content distributionnetwork(s) and/or application distribution network(s). A contentdistribution network (CDN) or an application distribution network (ADN)generally refers to a delivery system that includes a collection ofcomputers or computing devices linked by a network or networks. A CDN orADN can employ software, systems, protocols or techniques to facilitatevarious services, such as storage, caching, communication of content, orstreaming media or applications. A CDN or ADN can also enable an entityto operate or manage another's site infrastructure, in whole or in part.

The servers 106, 110, and 114 can include a device that includes aconfiguration to provide content such as interactive content via anetwork to another device. Such server(s) can, for example, host a site,service or an associated application, such as, an email platform (e.g.,Yahoo!® Mail), a social networking site, a photo sharing site/service(e.g., Tumblr®), a search platform or site, or a personal user site(such as a blog, vlog, online dating site, and the like) and the like.Such server(s) can also host a variety of other sites, including, butnot limited to business sites, educational sites, dictionary sites,encyclopedia sites, wikis, financial sites, government sites, and thelike. Devices that can operate as such server(s) include personalcomputers desktop computers, multiprocessor systems,microprocessor-based or programmable consumer electronics, network PCs,servers, and the like.

The servers 106, 110, and 114 can further provide a variety of servicesthat include, but are not limited to, streaming and/or downloading mediaservices, search services, email services, photo services, web services,social networking services, news services, third-party services, audioservices, video services, instant messaging (IM) services, SMS services,MMS services, FTP services, voice over IP (VOIP) services, or the like.Such services, for example a mail application and/or email-platform, canbe provided via the application server 108, whereby a user is able toutilize such service upon the user being authenticated, verified oridentified by the service. Examples of content can include videos, text,audio, images, or the like, which can be processed in the form ofphysical signals, such as electrical signals, for example, or can bestored in memory, as physical states, for example.

Also, servers 106, 110, and 114 can include an ad server such as aserver that stores online advertisements for presentation to users. “Adserving” provided by an ad server refers to methods used to place onlineadvertisements on websites, in applications, or other places where usersare more likely to see them, such as during an online session or duringcomputing platform use, for example. Various monetization techniques ormodels can be used in connection with sponsored advertising, includingadvertising associated with user. Such sponsored advertising includesmonetization techniques including sponsored search advertising,non-sponsored search advertising, guaranteed and non-guaranteed deliveryadvertising, ad networks/exchanges, ad targeting, ad serving and adanalytics. Such systems can incorporate near instantaneous auctions ofad placement opportunities during web page creation, (in some cases inless than 500 milliseconds) with higher quality ad placementopportunities resulting in higher revenues per ad. That is advertiserswill pay higher advertising rates when they believe their ads are beingplaced in or along with highly relevant content that is being presentedto users. Reductions in the time needed to quantify a high-quality adplacement offers ad platforms competitive advantages. Thus, higherspeeds and more relevant context detection improve these technologicalfields.

Servers 106, 110, and 114 can be capable of sending or receivingsignals, such as via a wired or wireless network, or can be capable ofprocessing or storing signals, such as in memory as physical memorystates. Devices capable of operating as a server can include, asexamples, dedicated rack-mounted servers, desktop computers, laptopcomputers, set top boxes, integrated devices combining various features,such as two or more features of the foregoing devices, or the like.Servers can vary widely in configuration or capabilities, but generally,a server can include one or more central processing units and memory. Aserver can also include one or more mass storage devices, one or morepower supplies, one or more wired or wireless network interfaces, one ormore input/output interfaces, or one or more operating systems, such asWindows Server, Mac OS X, Unix, Linux, FreeBSD, or the like.

In some embodiments, users are able to access services provided byservers 106, 110, and 114. This can include in a non-limiting example,authentication servers, search servers, email servers, social networkingservices servers, SMS servers, IM servers, MMS servers, exchangeservers, photo-sharing services servers, and travel services servers,via the network 105 using their various client devices. In someembodiments, applications, such as a mail or messaging application(e.g., Yahoo!® Mail, Yahoo!® Messenger), a photo sharing/user-generatedcontent (UGC) application (e.g., Flickr®, Tumblr®, and the like), astreaming video application (e.g., Netflix®, Hulu®, iTunes®, AmazonPrime®, HBO Go®, and the like), blog, photo or social networkingapplication (e.g., Facebook®, Twitter® and the like), search application(e.g., Yahoo!® Search), and the like, can be hosted by servers 106, 110,and 114. Thus, servers 106, 110, and 114 can store various types ofapplications and application related information including applicationdata and user profile information (e.g., identifying and behavioralinformation associated with a user). It should also be understood thatservers 106, 110, and 114 can also store various types of data relatedto content and services provided by an associated database. Embodimentsexist where the network 105 is also coupled with/connected to a TrustedSearch Server (TSS) which can be utilized to render content inaccordance with the embodiments discussed herein. Embodiments existwhere the TSS functionality can be embodied within servers 106, 110, and114.

Moreover, although FIG. 1 illustrates servers 106, 110, and 114 assingle computing devices, respectively, the disclosure is not solimited. For example, one or more functions of servers 106, 110, and 114can be distributed across one or more distinct computing devices.Moreover, in one embodiment, servers 106, 110, and 114 can be integratedinto a single computing device, without departing from the scope of thepresent disclosure.

FIG. 2 is a schematic diagram illustrating a computing device 200showing an example embodiment of a computing device that can be usedwithin the present disclosure. The computing device 200 can include manymore or less components than those shown in FIG. 2 . However, thecomponents shown are sufficient to disclose an illustrative embodimentfor implementing some aspects the present disclosure. The computingdevice can represent, for example, any one or more of the servers orclient devices discussed above in relation to FIG. 1 .

As shown in the figure, computing device 200 includes a processing unit(CPU) 222 in communication with a mass memory 230 via a bus 224.Computing device 200 also includes a power supply 226, one or morenetwork interfaces 250, and an input/output interface 260 (which caninclude an audio interface, a display, a keypad, an illuminator, aglobal positioning systems (GPS) receiver, sensors, and an input/outputinterface to such devices).

Power supply 226 provides power to computing device 200. A rechargeableor non-rechargeable battery can be used to provide power. The power canalso be provided by an external power source, such as an AC adapter or apowered docking cradle that supplements and/or recharges a battery.Computing device 200 can optionally communicate with a base station (notshown), or directly with another computing device. Network interface 250includes circuitry for coupling computing device 200 to one or morenetworks, and is constructed for use with one or more communicationprotocols and technologies as discussed above. Network interface 250 issometimes known as a transceiver, transceiving device, or networkinterface card (NIC). The input/output interface 260 can be used forcommunicating with external devices. Input/output interface 260 canutilize one or more communication technologies, such as USB, infrared,Bluetooth™, or the like.

Mass memory 230 includes a RAM 232, a ROM 234, and other storage means.Mass memory 230 illustrates another example of computer storage mediafor storage of information such as computer readable instructions, datastructures, program modules or other data. Mass memory 230 stores abasic input/output system (“BIOS”) 240 for controlling low-leveloperation of computing device 200. The mass memory also stores anoperating system 241 in RAM 232 for controlling the operation ofcomputing device 200. It will be appreciated that this component caninclude a general-purpose operating system such as a version of UNIX, orLINUX™, or a specialized client communication operating system such asWindows Client™, or the Symbian® operating system. The operating systemcan include, or interface with a Java virtual machine module thatenables control of hardware components and/or operating systemoperations via Java application programs.

The mass memory also stores a system browser in RAM 232 for controllingoperations of a system browser 243 and applications 242, such asenhanced video player 244 which can perform many of the operationsdescribed herein in relation to FIGS. 3-5 .

The enhanced video player 244 can include, be a part of, or be anon-transitory computer-readable storage medium tangibly encoded withcomputer-executable instructions, that when executed by processing unit222 of computing device 200, performs a method, the method includingsampling download rates performed by the player 244, the device 200,another video player, or another device over a certain network (such asnetwork 105). The sampling can occur prior to or during downloading andplaying of a first video segment (e.g., a current video segment) by theenhanced video player 244. The first video segment has a first videosegment quality. The method can also include determining a range ofdownload rates based at least on the sampled download rates. The methodcan also include determining an amount of accumulated video data in abuffer of the enhanced video player 244 immediately prior to or duringthe downloading of the first video segment. The method can also includemapping the amount of accumulated video data to a download rate withinthe determined range of download rates using a mapping function (such asa linear or stepwise mapping function). The method can also includedetermining a second video segment quality for a second video segment(e.g., a next or another future video segment) to be downloaded to theenhanced video player 244 after the downloading of the first videosegment based at least on the mapped download rate. After thedetermination of the second video segment quality, the enhanced videoplayer 244 can download and play the second video segment using thesecond video segment quality.

Memory 230 further includes one or more data stores, which can beutilized by computing device 200 to store, among other things, thesystem browser 243, the applications 242 and/or other data. For example,data stores can be employed to store information that describes variouscapabilities of computing device 200. The information can then beprovided to another device based on any of a variety of events,including being sent as part of a header during a communication, sentupon request, or the like. At least a portion of the capabilityinformation can also be stored on a disk drive or other storage medium(not shown) within computing device 200.

Applications 242 can include computer executable instructions which,when executed by computing device 200 or any of the other serversdescribed herein, transmit, receive, and/or otherwise process text,audio, video, images, and enable telecommunication with other serversand/or another user of another client device. Examples of applicationprograms or “apps” in some embodiments include browsers, calendars,contact managers, task managers, transcoders, photo management, databaseprograms, word processing programs, security applications, spreadsheetprograms, games, search programs, and so forth.

In some embodiments, the computing device 200 can include a processorand a non-transitory computer-readable storage medium for tangiblystoring thereon program logic for execution by the processor, theprogram logic having: executable logic for sampling download rates of avideo player prior to or during downloading of a first video segment tothe video player, the first video segment having a first video segmentquality; executable logic for determining a range of download rates ofthe video player based at least on the sampled download rates;executable logic for determining an amount of accumulated video data ina buffer of the video player immediately prior to or during thedownloading of the first video segment; executable logic for mapping theamount of accumulated video data to a download rate within thedetermined range of download rates using a mapping function; andexecutable logic for determining a second video segment quality for asecond video segment to be downloaded to the video player after thedownloading of the first video segment, based at least on the mappeddownload rate.

Having described components of the architecture example employed withinthe disclosed systems and methods, the components' operations withrespect to the disclosed systems and methods will now be described belowwith reference to FIGS. 3-5 .

In FIG. 3 , process 300 details steps performed by one or more computingdevices (such as one or more of the computing devices described herein),in accordance with some embodiments of the present disclosure.Specifically, the steps of process 300 can be performed by a digitalvideo player running on one or more computing devices (such as theenhanced video player 244). The steps are for selectively streamingvideo based on buffer data and download rates. Process 300 begins withstep 302, which includes a digital video player, such as enhanced videoplayer 244, or one or more other parts of one or more computing devices(such as devices 102-104 depicted in FIG. 1 ), downloading over anetwork (such as network 105) a first video segment (e.g., a currentvideo segment) with a first video segment quality (e.g., a current videosegment quality). The first video segment and other video segmentsdescribed herein can be downloaded from one or more servers (such asfrom the video content server 106, the video service server 110, and/orthe third server 114 depicted in FIG. 1 ).

In step 304, the video player (or one or more other parts of one or morecomputing devices) samples download rates of the video player prior toand/or during the downloading of the first video segment. In someembodiments, such as where sampling download rates of the video playeroccurs prior to the downloading of the first video segment, the process300, at step 305, can further include changing sampling rate of thesampling of download rates of the video player during the downloading ofthe first video segment according to the sampled download rates sampledprior to the downloading of the first video segment. Step 305 can beperformed by the video player or one or more other parts of one or morecomputing devices. The process 300 can further include changing samplingrate of the sampling of download rates of the video player during thedownloading of the first video segment according to data associated withvideo downloads by the video player. The input data for changingsampling rate can be associated with video downloads that occur beforeor during the downloading of the first video segment.

In step 306, the video player (or one or more other parts of one or morecomputing devices) determines a range of download rates of the videoplayer based at least on the sampled download rates. Step 306 can occurprior to, during, and/or after the downloading of the first videosegment depending on when the sampling of step 304 occurs. In someembodiments, such as where the sampling download rates of the videoplayer occur during and prior to the downloading of the first videosegment, the determining the range of download rates can be based atleast on the sampled download rates prior to and during the downloadingof the first video segment.

As shown in FIG. 4 , in some embodiments, the determining the range ofdownload rates, at step 306, can further include determining an upperpercentile of the sampled download rates, at step 402. The determiningthe range of download rates can further include determining a lowerpercentile of the sampled download rates, at step 404. The determiningthe range of download rates can further include limiting the range ofdownload rates to sampled rates within the upper percentile of thesampled download rates and at or above the lower percentile of thesampled download rates, at step 406. The determinations of the upper andlower percentiles can be configurable based on data associated withvideo downloads over the network such as downloads by the video player.Also, determinations of the upper and lower percentiles can beconfigurable based on a user input into the video player.

Determinations of the upper and lower percentiles can also bereconfigurable at least according to a determined second video segmentquality (e.g., a next or another future video segment quality) for asecond video segment (e.g., a next or another future video segment) tobe downloaded after the downloading of the first video segment. Thedetermined second video segment quality can be feedback input for thereconfigurations of the percentiles, as shown in step 408. Also, thedeterminations of the upper and lower percentiles can be based onpreselected upper and lower percentiles and/or corresponding weights.

As shown in FIG. 5 , in some embodiments, the determining the range ofdownload rates, at step 306, can further include determining respectivefrequencies of certain download rates or of certain ranges of downloadrates in the sampled download rates, at step 502. The determining therange of download rates can further include determining an upperpercentile of the sampled download rates based on the determinedfrequencies, at step 504. The determining the range of download ratescan also include determining a lower percentile of the sampled downloadrates based on the determined frequencies, at step 506. The determiningthe range of download rates can further include limiting the range ofdownload rates to sampled rates within the upper percentile of thesampled download rates and at or above the lower percentile of thesampled download rates, at step 508.

In step 308, the video player (or one or more other parts of one or morecomputing devices) determines an amount of accumulated video data in abuffer of the video player. Step 308 can occur prior to, during, and/orafter the downloading of the first video segment.

In step 310, the video player (or one or more other parts of one or morecomputing devices) maps the amount of accumulated video data to adownload rate within the determined range of download rates using amapping function (such as a linear mapping function or a stepwisemapping function). FIGS. 6-9 illustrate examples of the mapping using alinear mapping function. Step 310 can occur prior to, during, and/orafter the downloading of the first video segment; however, step 310occurs after steps 306 and 308 since steps 306 and 308 provide the inputfor the mapping of step 310.

In step 312, the video player (or one or more other parts of one or morecomputing devices) determines a second video segment quality (e.g., anext or another future video segment quality) for a second video segment(e.g., a next or another future video segment) to be downloaded afterthe downloading of the first video segment, based at least on the mappeddownload rate. FIG. 6 illustrates an example of the determining of thesecond video segment quality according to the example mapping shown inFIG. 7 , which is shown using a linear mapping function. Thedetermination of the second video segment quality for the second videosegment to be downloaded after the downloading of the first videosegment can also be based at least on video segment qualities availableto the video player. For example, the video player can retrieve thevideo segment qualities available through an interface with the displaydisplaying the video, and then further determine the second videosegment quality based at least on video segment qualities available tothe video player through the display. The interface with the display canbe or be included in a graphics or video rendering application of thedisplay.

Also, the video player (or one or more other parts of one or morecomputing devices) can determine the second video segment qualityfurther based on data size of the second video segment. For example, thesecond video segment quality can be determined based on the second videosegment being a number of bytes exceeding one or more thresholds thatmap to different second video segment qualities.

Example video segment qualities can include 1080p, 720p, 480p, 360p,240p, and 144p. Example video segment qualities can also include anytelevision resolution, such as 480i, 576i, 480p, 576p, HD, Full HDi,Full HD, 4K UHD, DCI 4K, 8K UHD. Also, example video segment qualitiescan include any computer display resolution, such as 1080p, 720p,1024×768 extended graphics array pixel resolution, 1280×1024 pixelresolution, 800×600 resolution, UXGA (1600×1200 resolution), QXGA(2048×1536 resolution), SXGA+ (1400×1050 resolution), WXGA (1280×800resolution), WSXGA+ (1680×1050 resolution), WUXGA (1920×1200resolution), 1366×768 resolution, 2560×1440 resolution, 2880×1800resolution, and 4096×2160 pixel resolution.

In step 314, the video player (or one or more other parts of one or morecomputing devices) downloads the second video segment with the secondvideo segment quality. In step 314, the video player (or one or moreother parts of one or more computing devices) downloads the second videosegment from a source over the network. The second video segment andother video segments described herein can be downloaded from one or moreservers (such as from the video content server 106, the video serviceserver 110, and/or the third server 114 depicted in FIG. 1 ) via anetwork (such as network 105). Alternatively, the video segments can bedownloaded through a peer-to-peer network, and the range of downloadrates can be determined analogously for the peer-to-peer network.

FIGS. 6-9 are schematic diagrams illustrating example operations inaccordance with some embodiments of the present disclosure.Specifically, FIG. 6 shows a depiction of a specific example of aspecific instance of the process 300 being used to choose the secondvideo segment quality from available qualities according to adetermination of buffer occupancy and mapping from the determined bufferoccupancy to a determined bandwidth range (the mapping depicted by theleft pair of dashed arrows and the one left solid arrow). Thedetermination and choosing of the second video segment quality in FIG. 6uses an additional mapping function. And, as shown by FIG. 6 , themapping functions used are linear mapping functions. In summary, FIG. 6shows the mapping of the determined buffer occupancy to the determinedbitrate download range as well as the choosing of the second videosegment quality based on the mapping results of the mapping from thedetermined buffer occupancy to the determined bandwidth range, and thenit shows mapping from the bandwidth range to the available video segmentqualities.

FIG. 7 specifically shows an example of how mapping to a range providesa better representation of an actual network's bandwidth which is shownas at least fluctuating from 1000 kbps to 4000 kbps.

FIG. 8 specifically shows an example of how the techniques describedherein prevent a determination of an empty or near empty buffer fromcausing drops in quality to the lowest quality available. This occursbecause the mapping with the bandwidth range directs the mapping to ahigher quality. This prevents unnecessary quality degradation.

FIG. 9 specifically shows an example of how the techniques describedherein prevent a determination of a full or almost full buffer fromcausing an over increase in the video quality to the highest qualityavailable. This occurs because the mapping with the bandwidth rangedirects the mapping to a slightly lower quality. This preventsunnecessary buffer draining and future unnecessary rebuffering issuesand delays.

For the purposes of this disclosure a module is a software, hardware, orfirmware (or combinations thereof) system, process or functionality, orcomponent thereof, that performs or facilitates the processes, features,and/or functions described herein (with or without human interaction oraugmentation). A module can include sub-modules. Software components ofa module can be stored on a computer readable medium for execution by aprocessor. Modules can be integral to one or more servers, or be loadedand executed by one or more servers. One or more modules can be groupedinto an engine or an application.

For the purposes of this disclosure the term “user”, “subscriber”“consumer” or “customer” should be understood to refer to a user of anapplication or applications as described herein and/or a consumer ofdata supplied by a data provider. By way of example, and not limitation,the term “user” or “subscriber” can refer to a person who receives dataprovided by the data or service provider over the Internet in a browsersession, or can refer to an automated software application whichreceives the data and stores or processes the data.

Those skilled in the art will recognize that the methods and systems ofthe present disclosure can be implemented in many manners and as suchare not to be limited by the foregoing exemplary embodiments andexamples. In other words, functional elements being performed by singleor multiple components, in various combinations of hardware and softwareor firmware, and individual functions, can be distributed among softwareapplications at either the client level or server level or both. In thisregard, any number of the features of the different embodimentsdescribed herein can be combined into single or multiple embodiments,and alternate embodiments having fewer than, or more than, all of thefeatures described herein are possible.

Functionality can also be, in whole or in part, distributed amongmultiple components, in manners now known or to become known. Thus,myriad software/hardware/firmware combinations are possible in achievingthe functions, features, interfaces and preferences described herein.Moreover, the scope of the present disclosure covers conventionallyknown manners for carrying out the described features and functions andinterfaces, as well as those variations and modifications that can bemade to the hardware or software or firmware components described hereinas would be understood by those skilled in the art now and hereafter.

Furthermore, the embodiments of methods presented and described asflowcharts in this disclosure are provided by way of example in order toprovide a more complete understanding of the technology. The disclosedmethods are not limited to the operations and logical flow presentedherein. Alternative embodiments are contemplated in which the order ofthe various operations is altered and in which sub-operations describedas being part of a larger operation are performed independently.

While various embodiments have been described for purposes of thisdisclosure, such embodiments should not be deemed to limit the teachingof this disclosure to those embodiments. Various changes andmodifications can be made to the elements and operations described aboveto obtain a result that remains within the scope of the systems andprocesses described in this disclosure.

What is claimed is:
 1. A method comprising: identifying, via a computingdevice, a plurality of download rates of a video player; determining,via the computing device, a range of download rates using the pluralityof identified download rates; and determining, via the computing device,a quality level for a video segment for download for the video player,the determining comprising: determining an amount of accumulated videodata in a buffer of the video player; identifying a download rate in therange of download rates using a first mapping that maps a buffer stateto the range of download rates, the determined amount of accumulatedvideo data representing the buffer state is mapped to the identifieddownload rate by the first mapping; and identifying the quality levelfor the video segment using a second mapping that maps the range ofdownload rates to video segment quality levels, the identified downloadrate being mapped to the identified video segment quality level by thesecond mapping.
 2. The method of claim 1, further comprising:identifying, via the computing device, a second plurality of downloadrates of the video player in connection with the video segment; using,via the computing device, the second plurality of download rates todetermine an updated range of download rates; and determining thequality level for a second video segment using the updated range ofdownload rates and the first and second mappings.
 3. The method of claim1, determining the range of download rates further comprising:determining upper and lower percentiles in connection with theidentified plurality of download rates; and determining the range ofdownload rates based on the determined upper and lower percentiles andthe plurality of identified download rates.
 4. The method of claim 3,wherein the range of download rates is representative of the identifieddownload rates, of the plurality of identified download rates, withinthe determined upper and lower percentiles.
 5. The method of claim 3,wherein the upper and lower percentiles are user configurable.
 6. Themethod of claim 3, wherein the upper and lower percentiles areconfigurable using data reflecting video downloads over a computernetwork used to download video data to the video player.
 7. The methodof claim 3, wherein the determined upper and lower percentiles arepreselected upper and lower percentiles.
 8. The method of claim 3,determining the upper and lower percentiles further comprises:determining respective frequencies of certain download rates or ofcertain ranges of download rates in the plurality of identified downloadrates; and determining the upper percentile and lower percentiles usingthe determined frequencies.
 9. The method of claim 1, identifying thevideo segment's quality level is further based on a data size of thevideo segment.
 10. The method of claim 1, wherein the first and secondmappings each comprise a mapping function.
 11. The method of claim 10,the mapping function is a linear mapping function.
 12. The method ofclaim 1, wherein the amount of accumulated video rate is indicative of alow-buffer state that maps to a lowest download rate in the range ofdownload rates via the first mapping, and the second mapping addressespossible degradations in quality by mapping the lowest download rate, inthe range of download rates, to a video segment quality level higherthan a lowest video segment quality level.
 13. The method of claim 1,wherein the amount of accumulated video rate is indicative of afull-buffer state that maps to a highest download rate in the range ofdownload rates via the first mapping, and the second mapping addressespossible buffer drainage by mapping the highest download rate, in therange of download rates, to a video segment quality level lower than ahighest video segment quality level.
 14. A non-transitorycomputer-readable storage medium tangibly encoded withcomputer-executable instructions, that when executed by a processor of acomputing device, performs a method, the method comprising: identifyinga plurality of download rates of a video player; determining a range ofdownload rates using the plurality of identified download rates; anddetermining a quality level for a video segment for download for thevideo player, the determining comprising: determining an amount ofaccumulated video data in a buffer of the video player; identifying adownload rate in the range of download rates using a first mapping thatmaps a buffer state to the range of download rates, the determinedamount of accumulated video data representing the buffer state is mappedto the identified download rate by the first mapping; and identifyingthe quality level for the video segment using a second mapping that mapsthe range of download rates to video segment quality levels, theidentified download rate being mapped to the identified video segmentquality level by the second mapping.
 15. The non-transitorycomputer-readable storage medium of claim 14, the method furthercomprising: identifying a second plurality of download rates of thevideo player in connection with the video segment; using the secondplurality of download rates to determine an updated range of downloadrates; and determining the quality for a second video segment using theupdated range of download rates and the first and second mappings. 16.The non-transitory computer-readable storage medium of claim 14,determining the range of download rates further comprising: determiningupper and lower percentiles in connection with the identified pluralityof download rates; and determining the range of download rates based onthe determined upper and lower percentiles and the plurality ofidentified download rates.
 17. The non-transitory computer-readablestorage medium of claim 16, determining the upper and lower percentilesfurther comprises: determining respective frequencies of certaindownload rates or of certain ranges of download rates in the pluralityof identified download rates; and determining the upper percentile andlower percentiles using the determined frequencies.
 18. Thenon-transitory computer-readable storage medium of claim 14, wherein theamount of accumulated video rate is indicative of a low-buffer statethat maps to a lowest download rate in the range of download rates viathe first mapping, and the second mapping addresses possibledegradations in quality by mapping the lowest download rate, in therange of download rates, to a video segment quality level higher than alowest video segment quality level.
 19. The non-transitorycomputer-readable storage medium of claim 14, wherein the amount ofaccumulated video rate is indicative of a full-buffer state that maps toa highest download rate in the range of download rates via the firstmapping, and the second mapping addresses possible buffer drainage bymapping the highest download rate, in the range of download rates, to avideo segment quality level lower than a highest video segment qualitylevel.
 20. A computing device, comprising: a processor; and anon-transitory computer-readable storage medium for tangibly storingthereon program logic for execution by the processor, the program logiccomprising: executable logic for identifying a plurality of downloadrates of a video player; executable logic for determining a range ofdownload rates using the plurality of identified download rates; andexecutable logic for determining a quality level for a video segment fordownload for the video player, the executable logic for determiningcomprising: executable logic for determining an amount of accumulatedvideo data in a buffer of the video player; executable logic foridentifying a download rate in the range of download rates using a firstmapping that maps a buffer state to the range of download rates, thedetermined amount of accumulated video data representing the bufferstate is mapped to the identified download rate by the first mapping;and executable logic for identifying the quality level for the videosegment using a second mapping that maps the range of download rates tovideo segment quality levels, the identified download rate being mappedto the identified video segment quality level by the second mapping.